The workflow triggers on push events on the 'master', 'main', and 'fix' branches, and runs on Ubuntu. It installs Make, caches the Cosmocc toolchain, sets up Cosmocc and Ape Loader, builds the project, makes a specific Llamafile, executes the Llama CLI CPU, and more.
Anthropic has introduced a new feature in their Console that allows users to generate production-ready prompt templates using AI. This feature employs prompt engineering techniques such as chain-of-thought reasoning, role setting, and clear variable delineation to create effective and precise prompts. It helps both new and experienced prompt engineers save time and often produces better results than hand-written prompts. The generated prompts are also editable for optimal performance.
Elia is a new open-source application designed for users who need an efficient, terminal-based way to interact with large language models (LLMs). The application allows users to chat with various models directly from their terminal and supports popular models like ChatGPT and Llama 3. Elia is highly keyboard-centric, stores conversations in a local SQLite database, and offers a simple setup via pipx.
The article argues that instead of developing numerous tools for LLM, giving it direct access to a terminal is more efficient and future-proof. It references Rich Sutton's "The Bitter Lesson" and discusses how the terminal's existing command-line tools can be utilized by LLM for various tasks, highlighting the importance of general methods over specialized tools.
The "LLM" toolkit offers a versatile command-line utility and Python library that allows users to work efficiently with large language models. Users can execute prompts directly from their terminals, store the outcomes in SQLite databases, generate embeddings, and perform various other tasks. In this extensive tutorial, topics covered include setup, usage, OpenAI models, alternative models, embeddings, plugins, model aliases, Python APIs, prompt templates, logging, related tools, CLI references, contributing, and change logs.
The "LLM" toolkit provides a command-line utility and Python library for interacting with large language models. It enables users to run prompts from the terminal, store responses in SQLite databases, generate embeddings, and more. This comprehensive guide includes topics such as setup, usage, OpenAI models, other models, embeddings, plugins, model aliases, Python API, prompt templates, logging, related tools, CLI reference, contributing, and changelog.
Use large language models embedded in single-file executables from the command line to perform tasks like renaming images based on their visual content
Llamafile lets you distribute and run LLMs with a single file
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